........................................Epoch: 1/200, Loss: 2.3941
........................................Epoch: 1/200, Loss: 2.0572
........................................Epoch: 1/200, Loss: 1.8963
........................................Epoch: 1/200, Loss: 1.8545
........................................Epoch: 1/200, Loss: 1.8011
........................................Epoch: 1/200, Loss: 1.7795
............................. Epoch 1 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 45.1913 %
Confusion matrix
[[ 0 2 1 4 3 3 193 85 0 0]
[ 0 278 1 2 1 0 0 2 1 5]
[ 0 85 73 45 19 0 18 13 1 37]
[ 0 27 22 41 16 5 118 34 17 10]
[ 0 6 0 8 242 4 0 11 15 4]
[ 0 2 1 14 51 30 59 104 28 1]
[ 0 1 3 12 0 1 225 48 0 0]
[ 0 3 0 8 21 10 100 138 8 1]
[ 0 7 1 12 27 14 7 31 189 2]
[ 0 112 26 26 17 0 6 8 0 95]]
........................................Epoch: 2/200, Loss: 1.4425
........................................Epoch: 2/200, Loss: 1.3861
........................................Epoch: 2/200, Loss: 1.3980
........................................Epoch: 2/200, Loss: 1.4177
........................................Epoch: 2/200, Loss: 1.3284
........................................Epoch: 2/200, Loss: 1.3401
............................. Epoch 2 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 50.0517 %
Confusion matrix
[[262 0 2 3 0 3 4 17 0 0]
[ 1 262 11 1 2 0 0 0 2 11]
[ 25 38 156 18 9 3 2 1 2 37]
[110 21 38 31 6 6 30 16 23 9]
[ 9 4 2 3 229 12 0 6 19 6]
[107 0 1 1 24 39 6 72 40 0]
[208 1 3 7 0 2 46 22 1 0]
[145 4 2 3 12 11 1 101 8 2]
[ 5 4 2 4 18 20 1 19 215 2]
[ 14 61 77 16 8 1 0 2 0 111]]
........................................Epoch: 3/200, Loss: 1.2670
........................................Epoch: 3/200, Loss: 1.2960
........................................Epoch: 3/200, Loss: 1.2667
........................................Epoch: 3/200, Loss: 1.2469
........................................Epoch: 3/200, Loss: 1.2447
........................................Epoch: 3/200, Loss: 1.2327
............................. Epoch 3 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 54.8432 %
Confusion matrix
[[ 31 0 2 7 4 41 100 105 0 1]
[ 0 251 23 3 2 1 0 0 1 9]
[ 0 26 174 22 7 10 5 12 1 34]
[ 5 12 28 80 6 27 53 61 3 15]
[ 0 1 3 2 251 20 0 5 3 5]
[ 3 0 2 4 33 159 23 64 2 0]
[ 7 1 2 10 0 17 198 55 0 0]
[ 3 1 2 4 13 76 23 166 1 0]
[ 0 2 0 6 32 92 0 10 146 2]
[ 1 23 93 14 9 4 0 11 0 135]]
........................................Epoch: 4/200, Loss: 1.2344
........................................Epoch: 4/200, Loss: 1.2432
........................................Epoch: 4/200, Loss: 1.1804
........................................Epoch: 4/200, Loss: 1.2161
........................................Epoch: 4/200, Loss: 1.1529
........................................Epoch: 4/200, Loss: 1.2364
............................. Epoch 4 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 56.9804 %
Confusion matrix
[[215 1 3 14 0 0 44 14 0 0]
[ 0 247 31 5 2 0 0 1 1 3]
[ 11 15 201 42 6 0 2 1 1 12]
[ 35 8 27 155 5 0 41 10 4 5]
[ 4 1 2 5 265 3 0 3 7 0]
[ 92 1 0 19 43 27 31 67 10 0]
[ 65 1 2 22 0 0 189 11 0 0]
[ 79 2 1 21 13 5 62 102 4 0]
[ 10 1 0 18 42 8 3 26 182 0]
[ 4 23 143 29 14 0 0 7 0 70]]
........................................Epoch: 5/200, Loss: 1.0633
........................................Epoch: 5/200, Loss: 1.1644
........................................Epoch: 5/200, Loss: 1.1438
........................................Epoch: 5/200, Loss: 1.1290
........................................Epoch: 5/200, Loss: 1.1742
........................................Epoch: 5/200, Loss: 1.1560
............................. Epoch 5 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 58.1524 %
Confusion matrix
[[250 0 1 5 0 12 11 12 0 0]
[ 0 273 5 0 0 0 1 1 1 9]
[ 27 31 130 26 0 2 4 1 1 69]
[ 75 13 14 96 1 9 41 16 11 14]
[ 5 3 2 13 167 67 0 8 19 6]
[ 66 0 1 5 4 127 12 61 12 2]
[124 0 4 7 0 4 129 22 0 0]
[ 84 2 0 8 0 36 14 138 4 3]
[ 2 2 0 6 4 52 0 20 201 3]
[ 9 48 24 25 2 2 0 4 0 176]]
........................................Epoch: 6/200, Loss: 1.1267
........................................Epoch: 6/200, Loss: 1.0937
........................................Epoch: 6/200, Loss: 1.1275
........................................Epoch: 6/200, Loss: 1.0814
........................................Epoch: 6/200, Loss: 1.1400
........................................Epoch: 6/200, Loss: 1.0711
............................. Epoch 6 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 62.4957 %
Confusion matrix
[[175 0 1 6 3 17 37 52 0 0]
[ 0 246 5 2 1 0 0 0 2 34]
[ 5 17 130 27 2 6 6 6 2 90]
[ 34 6 17 96 2 10 41 47 11 26]
[ 2 0 0 3 250 14 0 5 11 5]
[ 24 0 2 2 26 98 19 93 25 1]
[ 43 0 2 7 0 3 183 50 1 1]
[ 30 1 1 2 8 27 17 193 7 3]
[ 1 0 0 1 21 30 0 11 223 3]
[ 4 14 20 19 4 2 0 8 0 219]]
........................................Epoch: 7/200, Loss: 1.0754
........................................Epoch: 7/200, Loss: 1.0963
........................................Epoch: 7/200, Loss: 1.1692
........................................Epoch: 7/200, Loss: 1.0612
........................................Epoch: 7/200, Loss: 1.0542
........................................Epoch: 7/200, Loss: 1.1343
............................. Epoch 7 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 61.8063 %
Confusion matrix
[[209 0 0 4 4 10 35 26 3 0]
[ 0 267 2 2 2 0 0 1 1 15]
[ 17 24 99 15 7 4 8 5 2 110]
[ 48 12 14 93 6 6 43 32 14 22]
[ 3 0 0 2 258 6 0 4 13 4]
[ 36 0 1 1 34 64 22 91 40 1]
[ 60 1 3 10 0 0 184 30 2 0]
[ 45 1 0 2 13 12 30 177 8 1]
[ 1 1 0 1 24 17 1 11 233 1]
[ 5 33 8 17 7 2 1 8 0 209]]
........................................Epoch: 8/200, Loss: 1.0998
........................................Epoch: 8/200, Loss: 1.0950
........................................Epoch: 8/200, Loss: 1.0742
........................................Epoch: 8/200, Loss: 1.0438
........................................Epoch: 8/200, Loss: 1.0209
........................................Epoch: 8/200, Loss: 1.1202
............................. Epoch 8 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 61.8752 %
Confusion matrix
[[185 0 5 8 0 13 25 54 1 0]
[ 0 249 14 2 1 0 0 2 1 21]
[ 6 13 199 13 2 2 7 3 2 44]
[ 45 10 43 97 2 4 35 36 11 7]
[ 2 0 4 2 232 29 0 6 13 2]
[ 29 0 6 5 14 88 18 101 29 0]
[ 52 0 4 14 0 0 166 53 1 0]
[ 32 1 2 8 5 22 13 200 6 0]
[ 1 1 0 2 12 29 1 15 228 1]
[ 6 24 71 23 4 2 0 9 0 151]]
........................................Epoch: 9/200, Loss: 1.0213
........................................Epoch: 9/200, Loss: 1.0518
........................................Epoch: 9/200, Loss: 1.0211
........................................Epoch: 9/200, Loss: 1.0524
........................................Epoch: 9/200, Loss: 1.0023
........................................Epoch: 9/200, Loss: 1.1424
............................. Epoch 9 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 63.9090 %
Confusion matrix
[[161 0 0 10 1 27 50 41 0 1]
[ 0 259 3 5 1 0 0 1 1 20]
[ 7 17 98 35 2 7 8 4 1 112]
[ 20 7 3 147 3 12 35 39 2 22]
[ 0 1 0 3 250 21 0 3 7 5]
[ 23 0 0 9 20 141 21 66 10 0]
[ 33 0 2 11 0 5 190 49 0 0]
[ 26 1 0 6 8 36 17 190 3 2]
[ 1 1 0 6 20 45 1 23 188 5]
[ 2 20 5 21 2 3 2 5 0 230]]
........................................Epoch: 10/200, Loss: 1.0529
........................................Epoch: 10/200, Loss: 1.0207
........................................Epoch: 10/200, Loss: 1.0181
........................................Epoch: 10/200, Loss: 1.0489
........................................Epoch: 10/200, Loss: 1.0447
........................................Epoch: 10/200, Loss: 1.0824
............................. Epoch 10 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 62.8059 %
Confusion matrix
[[228 0 4 7 0 15 4 32 1 0]
[ 0 240 30 2 1 0 0 1 2 14]
[ 9 7 206 23 2 2 1 3 0 38]
[ 36 6 32 154 1 7 12 33 3 6]
[ 2 0 5 4 209 58 0 3 9 0]
[ 36 0 3 14 7 137 10 74 9 0]
[ 87 0 4 29 0 3 123 44 0 0]
[ 47 1 2 9 1 38 9 179 3 0]
[ 1 1 0 10 5 62 0 15 196 0]
[ 4 19 74 29 2 6 0 6 0 150]]
........................................Epoch: 11/200, Loss: 1.0066
........................................Epoch: 11/200, Loss: 1.0032
........................................Epoch: 11/200, Loss: 1.1060
........................................Epoch: 11/200, Loss: 0.9733
........................................Epoch: 11/200, Loss: 1.0350
........................................Epoch: 11/200, Loss: 0.9795
............................. Epoch 11 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 62.6680 %
Confusion matrix
[[204 0 0 3 1 16 28 37 1 1]
[ 0 249 18 0 1 0 1 1 1 19]
[ 14 12 153 15 0 3 5 4 3 82]
[ 57 6 16 85 2 14 46 27 13 24]
[ 2 1 1 2 219 30 0 8 21 6]
[ 25 0 0 2 11 99 18 100 34 1]
[ 73 0 3 7 0 3 169 34 1 0]
[ 43 1 0 4 3 26 18 187 6 1]
[ 1 0 0 1 9 17 0 23 234 5]
[ 9 15 27 8 1 3 3 5 0 219]]
........................................Epoch: 12/200, Loss: 0.9897
........................................Epoch: 12/200, Loss: 1.0708
........................................Epoch: 12/200, Loss: 0.9859
........................................Epoch: 12/200, Loss: 1.0027
........................................Epoch: 12/200, Loss: 1.0572
........................................Epoch: 12/200, Loss: 1.0006
............................. Epoch 12 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 63.8056 %
Confusion matrix
[[231 0 1 7 0 34 3 14 0 1]
[ 0 257 9 3 1 0 0 0 1 19]
[ 12 14 132 15 6 5 1 0 3 103]
[ 55 10 16 114 4 21 16 16 13 25]
[ 3 0 3 2 237 27 0 1 16 1]
[ 29 0 1 1 17 171 8 42 20 1]
[102 0 4 16 0 14 117 35 1 1]
[ 53 2 3 9 6 75 7 131 3 0]
[ 2 1 0 1 14 36 0 13 222 1]
[ 3 15 9 15 4 4 0 1 0 239]]
........................................Epoch: 13/200, Loss: 0.9758
........................................Epoch: 13/200, Loss: 0.9897
........................................Epoch: 13/200, Loss: 1.0740
........................................Epoch: 13/200, Loss: 0.9780
........................................Epoch: 13/200, Loss: 0.9524
........................................Epoch: 13/200, Loss: 1.0108
............................. Epoch 13 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.5295 %
Confusion matrix
[[170 0 3 7 2 46 46 15 1 1]
[ 0 264 11 1 2 0 0 0 2 10]
[ 4 17 128 11 5 9 6 2 3 106]
[ 28 10 11 108 5 20 45 21 15 27]
[ 0 0 2 2 250 23 0 3 7 3]
[ 16 0 1 1 17 176 20 33 25 1]
[ 42 1 2 9 0 17 193 23 1 2]
[ 26 1 2 3 9 76 27 134 8 3]
[ 0 1 0 1 18 37 0 7 225 1]
[ 2 36 6 12 2 4 2 1 1 224]]
........................................Epoch: 14/200, Loss: 1.0245
........................................Epoch: 14/200, Loss: 0.9878
........................................Epoch: 14/200, Loss: 0.9630
........................................Epoch: 14/200, Loss: 0.9856
........................................Epoch: 14/200, Loss: 1.0221
........................................Epoch: 14/200, Loss: 1.0024
............................. Epoch 14 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.2537 %
Confusion matrix
[[134 0 0 16 2 28 44 66 0 1]
[ 0 268 2 6 0 0 0 0 1 13]
[ 3 21 109 33 1 4 8 4 1 107]
[ 16 8 8 160 1 7 32 31 4 23]
[ 1 0 1 2 249 19 0 2 8 8]
[ 14 1 1 7 20 146 19 69 12 1]
[ 31 0 2 18 0 4 177 57 1 0]
[ 18 2 0 18 8 43 12 183 3 2]
[ 0 1 0 9 13 34 0 27 202 4]
[ 2 26 3 16 2 2 1 2 0 236]]
........................................Epoch: 15/200, Loss: 0.9707
........................................Epoch: 15/200, Loss: 0.9320
........................................Epoch: 15/200, Loss: 0.9580
........................................Epoch: 15/200, Loss: 0.9998
........................................Epoch: 15/200, Loss: 1.0349
........................................Epoch: 15/200, Loss: 0.9657
............................. Epoch 15 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.3916 %
Confusion matrix
[[178 0 0 3 2 26 53 28 1 0]
[ 0 261 8 5 3 0 0 1 2 10]
[ 9 14 154 20 11 12 10 6 2 53]
[ 40 5 13 111 5 19 46 35 5 11]
[ 2 0 0 3 246 27 0 3 9 0]
[ 20 0 1 0 13 156 22 60 17 1]
[ 37 0 1 2 0 5 201 44 0 0]
[ 32 1 0 2 5 46 22 177 3 1]
[ 1 1 0 3 12 47 1 17 207 1]
[ 6 25 42 10 9 9 5 7 0 177]]
........................................Epoch: 16/200, Loss: 0.9477
........................................Epoch: 16/200, Loss: 1.0086
........................................Epoch: 16/200, Loss: 0.9340
........................................Epoch: 16/200, Loss: 0.9325
........................................Epoch: 16/200, Loss: 0.9635
........................................Epoch: 16/200, Loss: 0.9838
............................. Epoch 16 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 65.3568 %
Confusion matrix
[[220 0 1 5 1 14 25 24 0 1]
[ 0 221 39 6 2 0 0 3 4 15]
[ 6 4 197 30 1 6 5 4 0 38]
[ 36 4 21 141 1 8 33 28 7 11]
[ 3 0 2 3 230 33 0 4 12 3]
[ 35 0 2 3 11 140 18 69 12 0]
[ 69 0 0 15 0 5 167 34 0 0]
[ 47 1 1 12 2 26 15 180 4 1]
[ 2 0 1 1 9 41 0 21 213 2]
[ 4 9 57 26 1 3 1 2 0 187]]
........................................Epoch: 17/200, Loss: 0.9784
........................................Epoch: 17/200, Loss: 0.9514
........................................Epoch: 17/200, Loss: 0.9579
........................................Epoch: 17/200, Loss: 0.9635
........................................Epoch: 17/200, Loss: 0.9341
........................................Epoch: 17/200, Loss: 0.9784
............................. Epoch 17 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.0807 %
Confusion matrix
[[185 0 2 8 3 25 23 43 1 1]
[ 0 270 9 0 3 0 0 0 1 7]
[ 6 22 175 12 5 6 3 4 2 56]
[ 41 18 24 114 4 14 18 29 13 15]
[ 2 3 0 2 262 13 0 1 5 2]
[ 20 0 2 1 29 159 10 55 13 1]
[ 57 2 2 13 0 7 164 44 1 0]
[ 27 4 1 6 9 51 9 177 4 1]
[ 0 1 0 1 27 42 0 9 209 1]
[ 3 32 30 13 3 3 1 3 0 202]]
........................................Epoch: 18/200, Loss: 0.9090
........................................Epoch: 18/200, Loss: 0.9459
........................................Epoch: 18/200, Loss: 0.9687
........................................Epoch: 18/200, Loss: 0.9453
........................................Epoch: 18/200, Loss: 0.9764
........................................Epoch: 18/200, Loss: 0.9882
............................. Epoch 18 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.2537 %
Confusion matrix
[[141 0 3 12 3 19 18 92 2 1]
[ 0 254 5 10 1 0 0 1 3 16]
[ 1 15 143 46 1 5 4 10 4 62]
[ 12 5 11 172 1 7 17 42 14 9]
[ 0 0 0 4 236 31 0 3 16 0]
[ 9 0 0 10 8 111 9 103 39 1]
[ 50 0 1 20 0 0 144 74 1 0]
[ 13 1 0 10 7 25 8 217 7 1]
[ 0 1 0 1 8 29 0 5 245 1]
[ 2 14 23 37 3 5 0 5 0 201]]
........................................Epoch: 19/200, Loss: 0.9251
........................................Epoch: 19/200, Loss: 0.9184
........................................Epoch: 19/200, Loss: 0.9309
........................................Epoch: 19/200, Loss: 0.9194
........................................Epoch: 19/200, Loss: 0.9566
........................................Epoch: 19/200, Loss: 0.9494
............................. Epoch 19 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 65.1155 %
Confusion matrix
[[225 0 1 5 4 19 7 29 1 0]
[ 0 250 16 2 5 0 0 0 6 11]
[ 6 8 135 28 13 9 4 5 4 79]
[ 44 8 13 133 5 11 15 34 10 17]
[ 3 0 0 3 263 12 0 0 9 0]
[ 27 0 1 2 31 118 9 73 28 1]
[ 98 0 1 9 0 4 132 46 0 0]
[ 37 1 0 7 8 36 6 188 5 1]
[ 1 1 0 1 18 24 0 12 232 1]
[ 4 18 11 24 12 3 0 5 0 213]]
........................................Epoch: 20/200, Loss: 0.9326
........................................Epoch: 20/200, Loss: 0.9175
........................................Epoch: 20/200, Loss: 0.9076
........................................Epoch: 20/200, Loss: 0.9543
........................................Epoch: 20/200, Loss: 0.9299
........................................Epoch: 20/200, Loss: 0.9973
............................. Epoch 20 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 65.9083 %
Confusion matrix
[[230 0 2 7 4 10 4 33 1 0]
[ 0 259 17 3 1 0 1 0 2 7]
[ 9 12 206 19 7 4 3 3 1 27]
[ 43 10 28 138 5 5 15 27 8 11]
[ 3 0 4 2 258 11 0 3 8 1]
[ 39 0 1 3 25 119 15 73 15 0]
[ 95 1 0 15 0 3 144 31 1 0]
[ 46 1 4 8 10 26 11 178 5 0]
[ 1 1 1 1 24 28 0 10 224 0]
[ 4 17 78 18 7 2 2 6 0 156]]
........................................Epoch: 21/200, Loss: 0.9134
........................................Epoch: 21/200, Loss: 0.9351
........................................Epoch: 21/200, Loss: 0.9037
........................................Epoch: 21/200, Loss: 0.9082
........................................Epoch: 21/200, Loss: 0.9286
........................................Epoch: 21/200, Loss: 0.9437
............................. Epoch 21 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 65.6670 %
Confusion matrix
[[181 0 0 7 1 14 42 44 1 1]
[ 0 269 4 4 0 0 0 1 1 11]
[ 9 25 108 36 1 6 2 9 0 95]
[ 28 7 4 158 2 11 24 40 3 13]
[ 2 0 1 2 228 29 0 9 13 6]
[ 20 0 0 6 10 135 11 88 20 0]
[ 43 0 0 5 0 7 175 60 0 0]
[ 24 1 0 7 1 29 8 213 4 2]
[ 1 2 0 4 14 28 0 20 221 0]
[ 3 31 3 24 1 6 1 4 0 217]]
........................................Epoch: 22/200, Loss: 0.8490
........................................Epoch: 22/200, Loss: 0.9230
........................................Epoch: 22/200, Loss: 0.8936
........................................Epoch: 22/200, Loss: 0.8986
........................................Epoch: 22/200, Loss: 0.9304
........................................Epoch: 22/200, Loss: 0.9446
............................. Epoch 22 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.8052 %
Confusion matrix
[[130 0 2 13 2 11 45 86 1 1]
[ 0 255 16 2 1 0 2 1 2 11]
[ 3 11 180 33 0 3 6 6 2 47]
[ 11 7 18 142 1 6 49 40 7 9]
[ 0 0 1 3 237 25 0 7 15 2]
[ 16 0 1 2 9 117 15 109 20 1]
[ 27 0 2 8 0 2 189 62 0 0]
[ 20 1 1 7 5 18 7 224 5 1]
[ 0 1 0 1 10 32 0 17 228 1]
[ 3 20 39 31 1 5 3 9 1 178]]
........................................Epoch: 23/200, Loss: 0.9086
........................................Epoch: 23/200, Loss: 0.9324
........................................Epoch: 23/200, Loss: 0.9050
........................................Epoch: 23/200, Loss: 0.9418
........................................Epoch: 23/200, Loss: 0.8607
........................................Epoch: 23/200, Loss: 0.9242
............................. Epoch 23 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.4250 %
Confusion matrix
[[194 0 2 10 5 19 41 19 0 1]
[ 0 252 19 3 1 0 0 2 1 12]
[ 2 11 174 24 4 9 6 5 3 53]
[ 17 5 16 158 4 12 36 24 4 14]
[ 2 0 1 2 253 20 0 2 9 1]
[ 24 0 1 4 23 143 18 59 17 1]
[ 46 0 2 14 0 3 200 24 1 0]
[ 31 1 2 13 12 38 22 163 7 0]
[ 0 1 0 2 20 28 0 8 230 1]
[ 2 26 35 20 7 3 2 6 0 189]]
........................................Epoch: 24/200, Loss: 0.9408
........................................Epoch: 24/200, Loss: 0.8978
........................................Epoch: 24/200, Loss: 0.8710
........................................Epoch: 24/200, Loss: 0.9013
........................................Epoch: 24/200, Loss: 0.9666
........................................Epoch: 24/200, Loss: 0.9406
............................. Epoch 24 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.9431 %
Confusion matrix
[[177 0 3 4 1 10 51 45 0 0]
[ 0 256 21 3 1 0 1 1 1 6]
[ 9 8 228 10 3 4 8 4 1 16]
[ 36 9 31 130 3 7 29 33 4 8]
[ 4 0 4 1 240 27 0 2 11 1]
[ 23 0 2 3 12 151 19 69 11 0]
[ 42 0 3 9 0 6 195 35 0 0]
[ 32 1 2 4 7 27 22 191 3 0]
[ 0 0 1 5 14 45 0 20 204 1]
[ 8 30 107 17 3 6 1 6 0 112]]
........................................Epoch: 25/200, Loss: 0.9253
........................................Epoch: 25/200, Loss: 0.8840
........................................Epoch: 25/200, Loss: 0.8845
........................................Epoch: 25/200, Loss: 0.9126
........................................Epoch: 25/200, Loss: 0.9135
........................................Epoch: 25/200, Loss: 0.8737
............................. Epoch 25 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.3220 %
Confusion matrix
[[241 0 0 10 2 6 18 12 1 1]
[ 0 254 20 5 1 0 1 0 2 7]
[ 9 10 204 20 3 4 3 3 0 35]
[ 37 8 26 147 3 5 28 20 4 12]
[ 3 0 5 3 247 19 0 1 10 2]
[ 58 0 2 2 20 111 23 48 25 1]
[ 83 0 2 10 0 2 181 12 0 0]
[ 63 1 2 7 7 20 48 134 6 1]
[ 2 1 1 2 17 16 0 6 243 2]
[ 6 25 67 20 3 2 3 2 0 162]]
........................................Epoch: 26/200, Loss: 0.9184
........................................Epoch: 26/200, Loss: 0.8830
........................................Epoch: 26/200, Loss: 0.8877
........................................Epoch: 26/200, Loss: 0.9417
........................................Epoch: 26/200, Loss: 0.8799
........................................Epoch: 26/200, Loss: 0.8755
............................. Epoch 26 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.6667 %
Confusion matrix
[[169 0 2 21 5 4 66 21 2 1]
[ 0 248 12 12 0 0 0 0 2 16]
[ 4 8 168 33 1 2 5 1 3 66]
[ 10 3 13 176 2 2 37 22 7 18]
[ 3 0 3 2 252 6 0 1 18 5]
[ 30 0 1 6 26 86 32 74 34 1]
[ 35 0 1 16 0 0 214 23 1 0]
[ 33 1 1 17 6 13 44 165 7 2]
[ 2 1 0 2 15 15 1 10 241 3]
[ 2 18 27 18 4 1 2 3 0 215]]
........................................Epoch: 27/200, Loss: 0.8420
........................................Epoch: 27/200, Loss: 0.8364
........................................Epoch: 27/200, Loss: 0.8789
........................................Epoch: 27/200, Loss: 0.9422
........................................Epoch: 27/200, Loss: 0.9173
........................................Epoch: 27/200, Loss: 0.8660
............................. Epoch 27 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 65.9428 %
Confusion matrix
[[224 0 3 3 3 25 11 20 1 1]
[ 0 237 26 2 5 0 1 0 3 16]
[ 6 6 189 9 6 7 5 2 0 61]
[ 44 4 34 87 6 13 33 35 12 22]
[ 3 0 0 2 261 10 0 0 12 2]
[ 29 0 2 0 31 139 8 50 30 1]
[ 82 0 1 4 0 5 164 33 1 0]
[ 38 1 2 0 12 47 11 172 6 0]
[ 1 1 1 0 21 17 1 7 239 2]
[ 4 10 49 5 5 5 3 7 1 201]]
........................................Epoch: 28/200, Loss: 0.8902
........................................Epoch: 28/200, Loss: 0.9504
........................................Epoch: 28/200, Loss: 0.8606
........................................Epoch: 28/200, Loss: 0.8738
........................................Epoch: 28/200, Loss: 0.8683
........................................Epoch: 28/200, Loss: 0.8074
............................. Epoch 28 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 60.9445 %
Confusion matrix
[[263 0 0 3 0 3 2 19 0 1]
[ 1 198 57 16 1 0 1 3 2 11]
[ 27 2 192 30 1 2 5 7 2 23]
[ 76 1 17 114 2 3 33 31 6 7]
[ 9 0 2 2 226 29 1 9 11 1]
[ 69 0 1 1 10 85 18 89 16 1]
[121 0 2 3 0 0 145 19 0 0]
[ 76 1 0 3 1 13 20 172 2 1]
[ 7 0 1 2 12 25 2 27 214 0]
[ 11 7 71 21 2 2 4 13 0 159]]
........................................Epoch: 29/200, Loss: 0.9153
........................................Epoch: 29/200, Loss: 0.8660
........................................Epoch: 29/200, Loss: 0.8776
........................................Epoch: 29/200, Loss: 0.8461
........................................Epoch: 29/200, Loss: 0.9211
........................................Epoch: 29/200, Loss: 0.8885
............................. Epoch 29 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.0800 %
Confusion matrix
[[180 0 4 10 3 23 37 33 1 0]
[ 0 247 23 4 3 0 1 1 2 9]
[ 3 7 189 29 2 6 4 3 3 45]
[ 11 4 20 161 2 7 31 34 9 11]
[ 1 0 2 3 248 15 0 4 17 0]
[ 20 0 1 4 14 141 18 63 29 0]
[ 42 0 2 10 0 6 196 34 0 0]
[ 23 1 2 7 8 34 24 182 8 0]
[ 0 1 0 3 14 22 0 4 245 1]
[ 3 13 45 23 3 5 3 9 0 186]]
........................................Epoch: 30/200, Loss: 0.8701
........................................Epoch: 30/200, Loss: 0.8777
........................................Epoch: 30/200, Loss: 0.8104
........................................Epoch: 30/200, Loss: 0.8962
........................................Epoch: 30/200, Loss: 0.8897
........................................Epoch: 30/200, Loss: 0.8894
............................. Epoch 30 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.5288 %
Confusion matrix
[[191 0 2 6 4 59 3 25 1 0]
[ 0 256 17 2 3 0 0 0 2 10]
[ 3 8 162 37 4 11 2 2 4 58]
[ 30 11 8 156 3 20 18 25 8 11]
[ 0 0 1 3 248 27 0 1 10 0]
[ 15 0 1 3 10 224 3 22 11 1]
[ 73 0 1 12 0 26 153 25 0 0]
[ 22 1 0 7 7 110 8 128 5 1]
[ 0 1 0 3 11 56 0 1 217 1]
[ 4 25 26 24 5 4 1 6 0 195]]
........................................Epoch: 31/200, Loss: 0.8717
........................................Epoch: 31/200, Loss: 0.8313
........................................Epoch: 31/200, Loss: 0.8570
........................................Epoch: 31/200, Loss: 0.8655
........................................Epoch: 31/200, Loss: 0.8450
........................................Epoch: 31/200, Loss: 0.9487
............................. Epoch 31 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 65.4947 %
Confusion matrix
[[216 0 0 11 11 6 28 19 0 0]
[ 0 267 12 4 3 0 0 0 1 3]
[ 5 17 193 29 7 4 4 4 1 27]
[ 31 10 22 157 10 4 24 19 7 6]
[ 3 0 0 1 277 4 0 0 5 0]
[ 35 0 2 6 60 83 18 67 19 0]
[ 68 0 0 11 0 3 184 24 0 0]
[ 47 2 3 7 20 23 21 161 5 0]
[ 2 1 0 1 37 17 0 8 223 1]
[ 4 33 71 23 14 2 1 3 0 139]]
........................................Epoch: 32/200, Loss: 0.8486
........................................Epoch: 32/200, Loss: 0.8503
........................................Epoch: 32/200, Loss: 0.8621
........................................Epoch: 32/200, Loss: 0.8925
........................................Epoch: 32/200, Loss: 0.8484
........................................Epoch: 32/200, Loss: 0.8669
............................. Epoch 32 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.9421 %
Confusion matrix
[[172 1 2 22 1 18 39 35 0 1]
[ 0 275 5 1 1 0 1 0 0 7]
[ 2 21 165 37 0 3 2 2 2 57]
[ 12 13 13 175 2 9 31 24 1 10]
[ 3 1 1 4 246 21 1 1 11 1]
[ 20 0 1 4 17 167 15 55 9 2]
[ 40 0 0 9 0 15 189 37 0 0]
[ 31 3 1 9 3 52 8 178 3 1]
[ 2 1 0 6 17 36 4 13 209 2]
[ 2 32 22 30 1 4 1 3 0 195]]
........................................Epoch: 33/200, Loss: 0.8574
........................................Epoch: 33/200, Loss: 0.8498
........................................Epoch: 33/200, Loss: 0.8929
........................................Epoch: 33/200, Loss: 0.8570
........................................Epoch: 33/200, Loss: 0.8570
........................................Epoch: 33/200, Loss: 0.8382
............................. Epoch 33 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 64.7018 %
Confusion matrix
[[202 0 0 4 2 22 33 28 0 0]
[ 0 233 33 6 3 0 2 6 2 5]
[ 9 5 183 33 7 9 12 9 1 23]
[ 43 4 10 120 3 5 48 40 8 9]
[ 3 0 0 3 239 21 0 2 22 0]
[ 24 0 1 1 10 139 20 72 22 1]
[ 52 0 0 2 0 4 190 42 0 0]
[ 33 0 0 1 4 32 18 197 3 1]
[ 1 1 0 1 8 39 0 13 223 4]
[ 8 15 57 26 10 6 4 13 0 151]]
........................................Epoch: 34/200, Loss: 0.7929
........................................Epoch: 34/200, Loss: 0.8657
........................................Epoch: 34/200, Loss: 0.8685
........................................Epoch: 34/200, Loss: 0.8903
........................................Epoch: 34/200, Loss: 0.8625
........................................Epoch: 34/200, Loss: 0.8332
............................. Epoch 34 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.9080 %
Confusion matrix
[[207 0 3 3 5 32 14 27 0 0]
[ 0 243 23 1 4 0 1 1 2 15]
[ 6 6 185 18 3 7 2 3 0 61]
[ 52 5 22 121 3 10 26 29 8 14]
[ 4 0 0 0 265 13 0 1 7 0]
[ 25 0 1 2 25 156 12 49 18 2]
[ 69 0 1 7 0 9 161 43 0 0]
[ 34 1 0 3 11 50 10 173 6 1]
[ 1 1 1 1 23 24 1 10 227 1]
[ 7 12 40 13 6 3 1 5 0 203]]
........................................Epoch: 35/200, Loss: 0.9048
........................................Epoch: 35/200, Loss: 0.8270
........................................Epoch: 35/200, Loss: 0.8589
........................................Epoch: 35/200, Loss: 0.8343
........................................Epoch: 35/200, Loss: 0.8557
........................................Epoch: 35/200, Loss: 0.8972
............................. Epoch 35 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.3564 %
Confusion matrix
[[168 0 2 8 3 29 25 56 0 0]
[ 0 276 3 2 3 0 1 0 1 4]
[ 4 23 141 30 3 10 3 7 3 67]
[ 25 15 11 138 2 14 25 39 8 13]
[ 3 0 0 1 253 21 0 1 10 1]
[ 15 0 1 1 13 179 12 61 7 1]
[ 49 0 0 6 0 8 175 52 0 0]
[ 16 2 0 3 7 52 10 197 1 1]
[ 0 1 0 3 13 57 0 13 201 2]
[ 2 35 19 17 2 10 2 6 0 197]]
........................................Epoch: 36/200, Loss: 0.8069
........................................Epoch: 36/200, Loss: 0.8214
........................................Epoch: 36/200, Loss: 0.8511
........................................Epoch: 36/200, Loss: 0.8555
........................................Epoch: 36/200, Loss: 0.8661
........................................Epoch: 36/200, Loss: 0.8324
............................. Epoch 36 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.6667 %
Confusion matrix
[[187 0 0 8 3 13 60 18 1 1]
[ 0 273 8 2 0 0 4 0 2 1]
[ 8 24 184 19 1 3 11 1 0 40]
[ 36 9 21 140 3 6 40 20 3 12]
[ 3 1 3 4 244 17 1 0 16 1]
[ 34 0 1 2 17 146 28 40 19 3]
[ 43 0 0 4 0 2 220 21 0 0]
[ 45 1 1 4 8 40 32 152 5 1]
[ 2 3 1 3 12 31 5 8 224 1]
[ 3 53 41 15 2 3 6 3 0 164]]
........................................Epoch: 37/200, Loss: 0.8203
........................................Epoch: 37/200, Loss: 0.8624
........................................Epoch: 37/200, Loss: 0.8386
........................................Epoch: 37/200, Loss: 0.8368
........................................Epoch: 37/200, Loss: 0.8608
........................................Epoch: 37/200, Loss: 0.9267
............................. Epoch 37 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.1489 %
Confusion matrix
[[195 0 0 10 1 16 49 16 3 1]
[ 0 255 19 2 1 0 0 0 2 11]
[ 5 9 203 27 1 6 8 1 4 27]
[ 27 4 16 161 3 9 34 15 12 9]
[ 2 1 1 1 237 28 0 2 16 2]
[ 27 0 1 3 12 144 19 45 38 1]
[ 44 0 0 10 0 5 213 17 1 0]
[ 39 1 1 5 8 43 41 141 9 1]
[ 2 1 0 1 8 17 1 5 255 0]
[ 2 18 63 21 3 5 1 4 0 173]]
........................................Epoch: 38/200, Loss: 0.8535
........................................Epoch: 38/200, Loss: 0.7963
........................................Epoch: 38/200, Loss: 0.8007
........................................Epoch: 38/200, Loss: 0.7970
........................................Epoch: 38/200, Loss: 0.8444
........................................Epoch: 38/200, Loss: 0.8725
............................. Epoch 38 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.3561 %
Confusion matrix
[[227 0 2 4 1 16 20 20 1 0]
[ 0 260 22 3 0 0 0 0 2 3]
[ 13 10 236 12 1 5 1 2 2 9]
[ 52 5 35 125 2 13 18 29 5 6]
[ 4 0 2 1 239 26 0 4 12 2]
[ 31 0 3 2 11 163 12 56 12 0]
[ 63 0 1 8 0 10 174 33 0 1]
[ 41 1 2 3 3 36 11 189 3 0]
[ 2 1 1 1 9 41 1 13 221 0]
[ 10 34 102 11 2 4 1 6 0 120]]
........................................Epoch: 39/200, Loss: 0.8870
........................................Epoch: 39/200, Loss: 0.8382
........................................Epoch: 39/200, Loss: 0.8499
........................................Epoch: 39/200, Loss: 0.8640
........................................Epoch: 39/200, Loss: 0.8372
........................................Epoch: 39/200, Loss: 0.8069
............................. Epoch 39 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.7356 %
Confusion matrix
[[237 0 0 22 1 8 10 12 0 1]
[ 0 261 15 2 0 0 1 0 2 9]
[ 4 12 159 38 1 5 1 2 2 67]
[ 23 7 8 211 2 2 14 5 4 14]
[ 2 0 1 7 242 20 0 2 14 2]
[ 50 0 1 20 15 134 8 36 23 3]
[110 0 1 38 0 6 121 14 0 0]
[ 84 3 2 35 4 38 10 107 5 1]
[ 2 1 0 5 12 17 1 5 245 2]
[ 2 13 23 26 3 2 1 1 0 219]]
........................................Epoch: 40/200, Loss: 0.8570
........................................Epoch: 40/200, Loss: 0.7921
........................................Epoch: 40/200, Loss: 0.8383
........................................Epoch: 40/200, Loss: 0.8159
........................................Epoch: 40/200, Loss: 0.8693
........................................Epoch: 40/200, Loss: 0.8559
............................. Epoch 40 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.6663 %
Confusion matrix
[[169 0 0 9 1 14 58 38 1 1]
[ 0 242 23 7 0 0 0 2 3 13]
[ 4 3 169 37 1 5 8 5 2 57]
[ 19 3 12 156 1 5 38 37 6 13]
[ 1 0 1 1 239 24 0 7 17 0]
[ 17 0 1 3 15 123 26 80 25 0]
[ 32 0 0 4 0 2 220 30 2 0]
[ 28 1 1 3 1 24 24 199 7 1]
[ 2 1 0 1 11 22 1 9 242 1]
[ 4 10 33 22 2 4 4 7 0 204]]
........................................Epoch: 41/200, Loss: 0.8315
........................................Epoch: 41/200, Loss: 0.7960
........................................Epoch: 41/200, Loss: 0.8330
........................................Epoch: 41/200, Loss: 0.8220
........................................Epoch: 41/200, Loss: 0.8066
........................................Epoch: 41/200, Loss: 0.8412
............................. Epoch 41 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.0114 %
Confusion matrix
[[243 0 0 6 1 13 11 16 0 1]
[ 0 264 8 1 2 0 0 2 2 11]
[ 15 14 170 21 6 3 6 3 1 52]
[ 58 8 18 127 5 7 30 16 6 15]
[ 4 0 0 0 257 22 0 0 6 1]
[ 39 0 1 1 19 143 19 56 11 1]
[ 99 0 1 4 0 3 170 13 0 0]
[ 69 3 1 4 4 32 20 154 2 0]
[ 2 1 1 0 20 28 2 11 219 6]
[ 9 21 32 14 4 6 2 5 0 197]]
........................................Epoch: 42/200, Loss: 0.8103
........................................Epoch: 42/200, Loss: 0.8236
........................................Epoch: 42/200, Loss: 0.8158
........................................Epoch: 42/200, Loss: 0.8716
........................................Epoch: 42/200, Loss: 0.8376
........................................Epoch: 42/200, Loss: 0.8423
............................. Epoch 42 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.9417 %
Confusion matrix
[[223 0 2 16 1 19 13 15 1 1]
[ 0 241 20 9 1 0 0 0 2 17]
[ 3 6 183 23 1 6 3 0 1 65]
[ 21 4 19 167 4 11 26 13 5 20]
[ 1 0 1 4 252 21 0 0 9 2]
[ 29 0 2 2 26 177 12 30 11 1]
[ 72 0 1 12 0 9 178 18 0 0]
[ 53 1 3 11 5 58 21 133 4 0]
[ 2 1 0 1 16 27 2 7 230 4]
[ 2 6 41 19 2 3 0 1 0 216]]
........................................Epoch: 43/200, Loss: 0.8486
........................................Epoch: 43/200, Loss: 0.7912
........................................Epoch: 43/200, Loss: 0.8256
........................................Epoch: 43/200, Loss: 0.8687
........................................Epoch: 43/200, Loss: 0.7940
........................................Epoch: 43/200, Loss: 0.8284
............................. Epoch 43 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.4250 %
Confusion matrix
[[205 0 0 8 1 20 35 20 1 1]
[ 0 265 9 3 3 0 0 1 3 6]
[ 8 14 132 50 2 11 9 6 3 56]
[ 34 6 4 158 2 14 29 30 5 8]
[ 3 0 0 1 250 17 0 1 16 2]
[ 19 0 1 1 17 175 18 46 12 1]
[ 59 0 0 7 0 12 191 21 0 0]
[ 34 1 0 4 5 50 28 162 4 1]
[ 1 1 0 4 11 31 2 6 234 0]
[ 5 28 21 34 4 4 3 7 0 184]]
........................................Epoch: 44/200, Loss: 0.8508
........................................Epoch: 44/200, Loss: 0.8314
........................................Epoch: 44/200, Loss: 0.7870
........................................Epoch: 44/200, Loss: 0.8009
........................................Epoch: 44/200, Loss: 0.8151
........................................Epoch: 44/200, Loss: 0.8103
............................. Epoch 44 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.1834 %
Confusion matrix
[[156 0 1 9 3 37 46 36 2 1]
[ 0 257 12 3 2 0 1 0 4 11]
[ 3 8 176 40 3 7 1 3 2 48]
[ 27 5 11 158 5 17 27 24 5 11]
[ 1 0 0 4 253 23 0 0 9 0]
[ 11 0 0 5 10 210 12 33 8 1]
[ 31 0 0 17 0 19 199 24 0 0]
[ 18 1 1 8 8 75 19 156 2 1]
[ 0 1 0 3 9 40 0 10 227 0]
[ 2 24 42 18 3 6 2 7 0 186]]
........................................Epoch: 45/200, Loss: 0.7653
........................................Epoch: 45/200, Loss: 0.8120
........................................Epoch: 45/200, Loss: 0.7763
........................................Epoch: 45/200, Loss: 0.8625
........................................Epoch: 45/200, Loss: 0.8506
........................................Epoch: 45/200, Loss: 0.8165
............................. Epoch 45 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.5629 %
Confusion matrix
[[229 0 0 3 1 21 12 24 1 0]
[ 0 247 17 7 1 0 1 6 4 7]
[ 9 6 208 23 1 7 7 7 2 21]
[ 49 4 18 139 2 11 27 22 12 6]
[ 1 0 2 1 227 34 0 4 21 0]
[ 24 0 1 1 2 168 10 60 23 1]
[ 78 0 1 7 0 9 163 31 1 0]
[ 40 0 0 2 3 43 8 187 6 0]
[ 2 1 0 1 7 27 0 10 242 0]
[ 6 25 63 25 2 9 2 8 0 150]]
........................................Epoch: 46/200, Loss: 0.7962
........................................Epoch: 46/200, Loss: 0.8210
........................................Epoch: 46/200, Loss: 0.7885
........................................Epoch: 46/200, Loss: 0.7762
........................................Epoch: 46/200, Loss: 0.8199
........................................Epoch: 46/200, Loss: 0.8216
............................. Epoch 46 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.4940 %
Confusion matrix
[[239 0 0 5 1 8 19 18 0 1]
[ 0 243 17 7 3 0 0 0 3 17]
[ 13 7 173 31 2 3 8 4 3 47]
[ 49 4 11 135 3 8 37 26 4 13]
[ 2 0 1 2 243 20 0 2 19 1]
[ 45 0 1 1 18 127 15 66 16 1]
[ 85 0 0 2 0 3 177 23 0 0]
[ 53 1 0 3 5 25 22 177 2 1]
[ 2 1 0 1 9 21 1 13 240 2]
[ 10 15 33 16 1 3 3 5 0 204]]
........................................Epoch: 47/200, Loss: 0.8276
........................................Epoch: 47/200, Loss: 0.7594
........................................Epoch: 47/200, Loss: 0.7951
........................................Epoch: 47/200, Loss: 0.7939
........................................Epoch: 47/200, Loss: 0.8443
........................................Epoch: 47/200, Loss: 0.8349
............................. Epoch 47 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.0452 %
Confusion matrix
[[177 0 0 13 1 25 31 41 2 1]
[ 0 274 4 1 0 0 0 1 2 8]
[ 2 20 137 42 0 7 3 5 3 72]
[ 18 9 9 164 3 13 24 25 11 14]
[ 0 0 0 1 250 25 0 3 10 1]
[ 16 0 1 4 9 156 11 71 21 1]
[ 40 0 0 14 0 8 186 41 1 0]
[ 18 1 0 6 5 38 14 200 6 1]
[ 1 1 0 1 11 24 0 7 244 1]
[ 2 27 13 20 2 6 1 4 0 215]]
........................................Epoch: 48/200, Loss: 0.7897
........................................Epoch: 48/200, Loss: 0.7864
........................................Epoch: 48/200, Loss: 0.8570
........................................Epoch: 48/200, Loss: 0.7590
........................................Epoch: 48/200, Loss: 0.7742
........................................Epoch: 48/200, Loss: 0.8279
............................. Epoch 48 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.5629 %
Confusion matrix
[[222 0 2 7 5 19 15 17 3 1]
[ 0 251 22 3 1 0 1 0 3 9]
[ 5 3 218 15 2 6 4 1 2 35]
[ 29 7 34 136 5 7 25 23 12 12]
[ 0 0 2 0 252 14 0 3 18 1]
[ 29 0 5 0 19 147 8 52 29 1]
[ 80 0 1 8 0 12 159 27 1 2]
[ 43 3 1 8 6 46 12 160 9 1]
[ 2 1 0 1 16 23 0 4 242 1]
[ 4 19 71 14 3 0 2 3 1 173]]
........................................Epoch: 49/200, Loss: 0.7863
........................................Epoch: 49/200, Loss: 0.7805
........................................Epoch: 49/200, Loss: 0.7751
........................................Epoch: 49/200, Loss: 0.7991
........................................Epoch: 49/200, Loss: 0.8230
........................................Epoch: 49/200, Loss: 0.8240
............................. Epoch 49 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.4936 %
Confusion matrix
[[187 0 4 23 7 19 27 22 2 0]
[ 0 248 25 2 3 0 0 0 4 8]
[ 2 3 223 21 3 2 3 3 4 27]
[ 12 6 22 186 7 8 18 16 5 10]
[ 0 0 0 3 267 6 0 2 12 0]
[ 23 0 4 6 36 135 9 41 35 1]
[ 48 0 1 27 0 5 176 30 3 0]
[ 29 1 3 15 10 43 23 154 9 2]
[ 2 1 0 1 28 8 1 5 243 1]
[ 2 14 73 22 5 3 1 2 0 168]]
........................................Epoch: 50/200, Loss: 0.8154
........................................Epoch: 50/200, Loss: 0.7973
........................................Epoch: 50/200, Loss: 0.8052
........................................Epoch: 50/200, Loss: 0.7922
........................................Epoch: 50/200, Loss: 0.8052
........................................Epoch: 50/200, Loss: 0.7674
............................. Epoch 50 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.5629 %
Confusion matrix
[[206 0 0 8 1 11 39 25 0 1]
[ 0 245 25 4 0 0 2 2 1 11]
[ 7 6 193 36 0 3 7 3 0 36]
[ 34 4 16 155 2 8 34 22 5 10]
[ 3 0 2 6 216 32 0 7 24 0]
[ 28 0 1 3 8 159 13 65 12 1]
[ 47 0 0 12 0 6 196 29 0 0]
[ 40 1 1 13 1 29 23 177 2 2]
[ 2 1 0 2 4 39 3 10 228 1]
[ 4 14 44 28 1 6 3 5 0 185]]
........................................Epoch: 51/200, Loss: 0.8032
........................................Epoch: 51/200, Loss: 0.7590
........................................Epoch: 51/200, Loss: 0.7871
........................................Epoch: 51/200, Loss: 0.7960
........................................Epoch: 51/200, Loss: 0.7956
........................................Epoch: 51/200, Loss: 0.8030
............................. Epoch 51 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.9421 %
Confusion matrix
[[148 0 5 11 5 16 40 60 5 1]
[ 0 241 26 3 2 0 0 0 4 14]
[ 2 3 211 16 1 4 4 4 5 41]
[ 25 4 28 150 3 13 21 23 10 13]
[ 1 0 2 1 243 22 0 3 18 0]
[ 14 0 3 1 18 157 9 59 26 3]
[ 31 0 0 15 0 12 182 47 2 1]
[ 18 1 2 3 12 40 16 188 9 0]
[ 1 1 0 1 16 24 0 5 241 1]
[ 2 10 49 9 3 6 0 1 0 210]]
........................................Epoch: 52/200, Loss: 0.7515
........................................Epoch: 52/200, Loss: 0.8233
........................................Epoch: 52/200, Loss: 0.7694
........................................Epoch: 52/200, Loss: 0.8715
........................................Epoch: 52/200, Loss: 0.7917
........................................Epoch: 52/200, Loss: 0.7977
............................. Epoch 52 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.2520 %
Confusion matrix
[[203 0 0 5 1 18 27 35 1 1]
[ 0 258 15 3 0 0 0 1 2 11]
[ 6 9 165 26 1 6 9 3 2 64]
[ 31 5 18 135 4 13 41 26 4 13]
[ 2 0 0 1 252 22 1 2 9 1]
[ 24 0 2 2 15 150 9 67 19 2]
[ 51 0 0 4 0 7 198 30 0 0]
[ 29 1 0 7 4 33 24 187 3 1]
[ 1 1 0 2 12 24 1 8 240 1]
[ 2 15 22 17 1 5 4 3 0 221]]
........................................Epoch: 53/200, Loss: 0.7639
........................................Epoch: 53/200, Loss: 0.7478
........................................Epoch: 53/200, Loss: 0.8280
........................................Epoch: 53/200, Loss: 0.8288
........................................Epoch: 53/200, Loss: 0.7446
........................................Epoch: 53/200, Loss: 0.7900
............................. Epoch 53 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.2182 %
Confusion matrix
[[170 0 1 5 5 8 47 51 4 0]
[ 0 257 21 2 0 0 2 2 4 2]
[ 7 9 226 11 2 3 7 5 5 16]
[ 28 5 33 112 5 12 39 34 14 8]
[ 0 0 3 0 244 10 0 5 28 0]
[ 18 0 3 2 17 118 12 86 34 0]
[ 33 0 0 2 0 5 214 34 2 0]
[ 25 1 2 0 7 14 29 208 3 0]
[ 1 1 1 1 15 11 1 10 248 1]
[ 3 25 84 7 4 4 5 5 0 153]]
........................................Epoch: 54/200, Loss: 0.7849
........................................Epoch: 54/200, Loss: 0.7988
........................................Epoch: 54/200, Loss: 0.7936
........................................Epoch: 54/200, Loss: 0.7832
........................................Epoch: 54/200, Loss: 0.7529
........................................Epoch: 54/200, Loss: 0.7791
............................. Epoch 54 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.1486 %
Confusion matrix
[[165 0 1 11 6 6 61 38 3 0]
[ 0 266 13 2 0 0 0 1 2 6]
[ 6 14 200 23 0 3 10 2 3 30]
[ 22 5 15 157 4 4 40 23 11 9]
[ 1 1 1 2 259 6 2 2 16 0]
[ 17 0 0 5 26 92 21 86 43 0]
[ 21 0 0 8 0 2 228 29 2 0]
[ 25 1 1 7 6 12 29 197 10 1]
[ 2 1 0 1 17 5 2 6 255 1]
[ 2 22 45 22 2 2 2 5 1 187]]
........................................Epoch: 55/200, Loss: 0.7689
........................................Epoch: 55/200, Loss: 0.8223
........................................Epoch: 55/200, Loss: 0.7640
........................................Epoch: 55/200, Loss: 0.7983
........................................Epoch: 55/200, Loss: 0.7836
........................................Epoch: 55/200, Loss: 0.8026
............................. Epoch 55 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.7697 %
Confusion matrix
[[229 0 1 12 7 6 25 10 1 0]
[ 0 273 6 6 0 0 0 0 2 3]
[ 8 19 160 39 3 4 5 1 1 51]
[ 36 7 8 174 5 5 24 12 8 11]
[ 4 1 0 0 266 6 0 0 12 1]
[ 54 0 1 3 39 111 14 40 24 4]
[ 76 0 0 8 0 6 178 22 0 0]
[ 72 2 0 18 11 30 18 135 3 0]
[ 2 1 0 1 23 8 0 6 248 1]
[ 5 40 15 25 4 3 3 3 0 192]]
........................................Epoch: 56/200, Loss: 0.7567
........................................Epoch: 56/200, Loss: 0.7965
........................................Epoch: 56/200, Loss: 0.8304
........................................Epoch: 56/200, Loss: 0.8545
........................................Epoch: 56/200, Loss: 0.7481
........................................Epoch: 56/200, Loss: 0.8204
............................. Epoch 56 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.0107 %
Confusion matrix
[[207 0 1 9 5 15 17 33 3 1]
[ 0 273 4 1 0 0 0 0 4 8]
[ 5 19 171 15 2 8 3 2 5 61]
[ 28 9 16 146 2 14 22 24 10 19]
[ 2 1 1 0 252 11 0 1 21 1]
[ 30 0 2 3 21 138 9 48 37 2]
[ 70 0 0 6 0 10 169 32 2 1]
[ 34 1 2 5 6 42 12 178 6 3]
[ 2 0 0 1 13 16 0 3 255 0]
[ 2 25 26 15 2 3 2 2 0 213]]
........................................Epoch: 57/200, Loss: 0.7401
........................................Epoch: 57/200, Loss: 0.7642
........................................Epoch: 57/200, Loss: 0.8141
........................................Epoch: 57/200, Loss: 0.7915
........................................Epoch: 57/200, Loss: 0.7865
........................................Epoch: 57/200, Loss: 0.7770
............................. Epoch 57 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.1144 %
Confusion matrix
[[206 0 0 12 7 14 22 29 1 0]
[ 0 267 8 4 1 0 0 0 3 7]
[ 7 11 126 49 4 5 5 6 2 76]
[ 21 6 5 178 3 11 23 22 7 14]
[ 3 0 0 1 272 9 0 1 4 0]
[ 24 0 0 4 30 143 11 59 17 2]
[ 65 0 0 15 0 8 172 29 0 1]
[ 34 3 0 10 12 33 13 175 7 2]
[ 2 1 0 4 21 26 0 8 227 1]
[ 3 22 10 32 6 2 2 3 0 210]]
........................................Epoch: 58/200, Loss: 0.7749
........................................Epoch: 58/200, Loss: 0.8199
........................................Epoch: 58/200, Loss: 0.8326
........................................Epoch: 58/200, Loss: 0.7810
........................................Epoch: 58/200, Loss: 0.7402
........................................Epoch: 58/200, Loss: 0.7850
............................. Epoch 58 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.0796 %
Confusion matrix
[[211 0 0 10 3 17 26 23 1 0]
[ 0 256 8 11 1 0 0 1 4 9]
[ 12 11 192 25 3 3 2 2 3 38]
[ 38 4 11 152 2 8 28 24 14 9]
[ 4 0 0 0 250 21 0 0 14 1]
[ 26 0 1 1 13 154 13 51 29 2]
[ 70 0 0 7 0 6 178 26 2 1]
[ 39 2 0 4 4 42 17 171 9 1]
[ 3 1 0 1 12 17 1 2 253 0]
[ 3 19 44 26 1 4 2 4 0 187]]
........................................Epoch: 59/200, Loss: 0.7464
........................................Epoch: 59/200, Loss: 0.7968
........................................Epoch: 59/200, Loss: 0.7702
........................................Epoch: 59/200, Loss: 0.7532
........................................Epoch: 59/200, Loss: 0.8307
........................................Epoch: 59/200, Loss: 0.8392
............................. Epoch 59 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 70.1482 %
Confusion matrix
[[207 0 2 9 4 18 30 20 0 1]
[ 0 266 6 2 1 0 0 0 3 12]
[ 6 15 164 27 2 5 5 0 4 63]
[ 26 3 13 170 3 14 22 15 7 17]
[ 3 0 0 2 260 9 0 0 15 1]
[ 28 0 1 2 21 180 7 32 16 3]
[ 49 0 0 6 0 17 188 29 0 1]
[ 37 2 1 9 5 63 18 147 6 1]
[ 2 1 0 1 17 34 1 4 227 3]
[ 4 11 19 18 1 6 3 2 0 226]]
........................................Epoch: 60/200, Loss: 0.7014
........................................Epoch: 60/200, Loss: 0.7563
........................................Epoch: 60/200, Loss: 0.7912
........................................Epoch: 60/200, Loss: 0.7540
........................................Epoch: 60/200, Loss: 0.7796
........................................Epoch: 60/200, Loss: 0.8003
............................. Epoch 60 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.3561 %
Confusion matrix
[[191 0 0 12 2 15 12 59 0 0]
[ 0 251 19 8 1 0 0 2 3 6]
[ 6 4 180 55 3 6 4 6 3 24]
[ 25 3 4 186 2 10 18 29 8 5]
[ 0 0 1 2 231 18 0 11 27 0]
[ 15 0 1 2 8 140 7 94 22 1]
[ 62 0 0 16 0 9 152 50 0 1]
[ 24 0 1 6 1 33 6 213 4 1]
[ 2 1 0 1 9 21 0 11 244 1]
[ 4 16 41 47 2 4 1 9 0 166]]
........................................Epoch: 61/200, Loss: 0.7629
........................................Epoch: 61/200, Loss: 0.7787
........................................Epoch: 61/200, Loss: 0.7265
........................................Epoch: 61/200, Loss: 0.7749
........................................Epoch: 61/200, Loss: 0.7908
........................................Epoch: 61/200, Loss: 0.7571
............................. Epoch 61 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.3554 %
Confusion matrix
[[224 0 2 8 6 21 15 13 2 0]
[ 0 261 17 3 1 0 0 0 3 5]
[ 6 9 218 19 2 7 3 2 1 24]
[ 31 7 25 164 4 15 16 14 8 6]
[ 3 0 1 1 268 7 0 0 10 0]
[ 26 0 2 2 28 164 8 30 29 1]
[ 69 0 0 14 0 10 174 20 3 0]
[ 46 1 2 8 9 62 15 139 7 0]
[ 2 1 0 1 20 10 1 3 251 1]
[ 3 19 76 26 6 5 2 4 0 149]]
........................................Epoch: 62/200, Loss: 0.7713
........................................Epoch: 62/200, Loss: 0.7512
........................................Epoch: 62/200, Loss: 0.7755
........................................Epoch: 62/200, Loss: 0.7751
........................................Epoch: 62/200, Loss: 0.7307
........................................Epoch: 62/200, Loss: 0.7274
............................. Epoch 62 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.1486 %
Confusion matrix
[[197 0 3 7 3 13 29 38 0 1]
[ 0 242 27 3 2 0 0 0 2 14]
[ 4 4 222 6 1 1 2 2 0 49]
[ 26 3 48 129 3 5 30 21 4 21]
[ 3 0 1 1 253 12 0 1 15 4]
[ 20 0 6 0 16 136 22 76 10 4]
[ 47 0 0 8 0 3 207 25 0 0]
[ 29 1 4 4 5 24 30 186 5 1]
[ 2 1 0 0 16 27 1 7 231 5]
[ 3 11 60 6 1 1 2 3 0 203]]
........................................Epoch: 63/200, Loss: 0.7477
........................................Epoch: 63/200, Loss: 0.7941
........................................Epoch: 63/200, Loss: 0.7935
........................................Epoch: 63/200, Loss: 0.7640
........................................Epoch: 63/200, Loss: 0.7725
........................................Epoch: 63/200, Loss: 0.7746
............................. Epoch 63 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 66.7356 %
Confusion matrix
[[209 0 0 4 7 16 31 23 1 0]
[ 0 261 6 6 2 0 0 3 5 7]
[ 6 15 136 23 6 10 9 11 3 72]
[ 39 3 8 114 6 15 34 33 18 20]
[ 3 0 0 1 272 8 0 0 6 0]
[ 24 0 0 0 34 138 14 50 28 2]
[ 55 0 0 3 0 10 194 27 0 1]
[ 39 1 0 1 8 43 22 170 4 1]
[ 2 1 0 0 21 16 0 6 242 2]
[ 5 21 15 16 12 7 4 10 0 200]]
........................................Epoch: 64/200, Loss: 0.7397
........................................Epoch: 64/200, Loss: 0.7428
........................................Epoch: 64/200, Loss: 0.7207
........................................Epoch: 64/200, Loss: 0.7926
........................................Epoch: 64/200, Loss: 0.7295
........................................Epoch: 64/200, Loss: 0.7687
............................. Epoch 64 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.4243 %
Confusion matrix
[[220 0 0 20 1 7 23 19 0 1]
[ 0 260 14 4 0 0 0 0 2 10]
[ 3 5 184 47 1 3 1 1 3 43]
[ 22 3 15 209 1 7 11 11 2 9]
[ 1 1 1 9 224 19 0 1 29 5]
[ 35 0 2 12 6 148 11 47 26 3]
[ 71 0 0 21 0 3 178 17 0 0]
[ 41 1 2 28 2 41 14 155 5 0]
[ 3 2 0 4 9 20 2 4 244 2]
[ 3 19 37 30 1 4 2 2 0 192]]
........................................Epoch: 65/200, Loss: 0.7553
........................................Epoch: 65/200, Loss: 0.7642
........................................Epoch: 65/200, Loss: 0.7776
........................................Epoch: 65/200, Loss: 0.8055
........................................Epoch: 65/200, Loss: 0.7804
........................................Epoch: 65/200, Loss: 0.7665
............................. Epoch 65 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.6660 %
Confusion matrix
[[222 0 4 8 5 31 2 17 1 1]
[ 0 268 8 3 0 0 0 0 2 9]
[ 3 13 203 14 2 6 1 2 4 43]
[ 37 7 28 142 6 11 6 22 14 17]
[ 1 0 3 1 260 10 0 1 13 1]
[ 21 0 2 2 25 188 6 29 15 2]
[103 0 1 15 0 14 122 31 3 1]
[ 35 3 1 7 8 76 3 144 7 5]
[ 2 1 0 0 18 23 0 2 243 1]
[ 2 25 41 12 2 5 1 2 0 200]]
........................................Epoch: 66/200, Loss: 0.7365
........................................Epoch: 66/200, Loss: 0.7708
........................................Epoch: 66/200, Loss: 0.7544
........................................Epoch: 66/200, Loss: 0.7542
........................................Epoch: 66/200, Loss: 0.7811
........................................Epoch: 66/200, Loss: 0.7049
............................. Epoch 66 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.2520 %
Confusion matrix
[[148 0 1 6 8 14 64 46 3 1]
[ 0 259 15 2 2 0 2 3 2 5]
[ 4 8 182 26 1 3 7 6 4 50]
[ 21 5 17 150 5 13 34 27 7 11]
[ 2 0 0 2 263 11 0 1 10 1]
[ 13 0 2 3 30 146 17 52 25 2]
[ 22 0 0 3 0 9 228 27 0 1]
[ 17 1 1 5 10 36 28 185 5 1]
[ 2 1 0 1 17 16 2 4 245 2]
[ 2 24 32 12 3 4 3 7 0 203]]
........................................Epoch: 67/200, Loss: 0.7665
........................................Epoch: 67/200, Loss: 0.7248
........................................Epoch: 67/200, Loss: 0.7164
........................................Epoch: 67/200, Loss: 0.7237
........................................Epoch: 67/200, Loss: 0.7462
........................................Epoch: 67/200, Loss: 0.7970
............................. Epoch 67 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 68.7694 %
Confusion matrix
[[208 0 2 5 5 31 21 18 1 0]
[ 0 249 25 3 1 0 1 2 3 6]
[ 6 5 207 16 2 6 3 3 3 40]
[ 44 5 26 128 7 16 26 23 6 9]
[ 3 0 0 0 266 12 0 1 8 0]
[ 17 0 2 1 30 182 6 31 19 2]
[ 58 0 0 2 0 32 179 18 0 1]
[ 31 1 2 3 9 75 11 150 6 1]
[ 2 1 0 1 24 20 3 6 232 1]
[ 6 21 40 13 3 6 3 4 0 194]]
........................................Epoch: 68/200, Loss: 0.7438
........................................Epoch: 68/200, Loss: 0.7870
........................................Epoch: 68/200, Loss: 0.7292
........................................Epoch: 68/200, Loss: 0.7380
........................................Epoch: 68/200, Loss: 0.7737
........................................Epoch: 68/200, Loss: 0.7562
............................. Epoch 68 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 67.7353 %
Confusion matrix
[[229 0 0 6 4 10 28 13 1 0]
[ 0 262 17 1 2 0 0 1 4 3]
[ 12 8 212 23 4 3 8 3 4 14]
[ 50 5 25 119 6 11 32 18 15 9]
[ 2 0 0 1 265 11 0 1 10 0]
[ 35 0 2 2 23 141 20 45 20 2]
[ 72 0 0 4 0 3 197 13 0 1]
[ 63 1 1 1 8 32 29 148 6 0]
[ 2 1 0 1 15 23 0 4 243 1]
[ 8 29 72 13 7 4 3 5 0 149]]
........................................Epoch: 69/200, Loss: 0.7107
........................................Epoch: 69/200, Loss: 0.7567
........................................Epoch: 69/200, Loss: 0.7904
........................................Epoch: 69/200, Loss: 0.7824
........................................Epoch: 69/200, Loss: 0.8033
........................................Epoch: 69/200, Loss: 0.7657
............................. Epoch 69 completed
----------------------------------------
----------------------------------------
-----------
Accuracy: 69.2865 %
Confusion matrix
[[197 0 1 11 4 12 30 34 2 0]
[ 0 257 17 6 0 0 0 1 2 7]
[ 4 6 196 21 3 4 3 6 2 46]
[ 32 6 29 136 5 8 26 17 12 19]
[ 2 0 2 1 260 7 0 3 14 1]
[ 19 0 2 1 24 125 16 71 30 2]
[ 54 0 0 4 0 3 197 28 3 1]
[ 30 2 1 5 10 28 14 191 7 1]
[ 2 2 0 1 18 9 0 5 253 0]
[ 2 25 35 17 4 5 2 2 0 198]]
No improvement for 10 epochs